Digital Commons Network^™

Essays On Foreign Direct Investment, Free Trade Agreements, And The Digital Economy, Constance Vigilance

Dissertations

Economic globalization’s key components include international trade, foreign direct investment (FDI), and the digital economy. FDI stimulates export growth, complementing international trade. The global economy is being transformed by digitalization, boosting international trade and GDP through speed, convenience, productivity, and transparency and driving shifts in FDI patterns through resource-efficient products and green technologies.

This dissertation investigates three prominent issues - the FDI inflows to fragile, least-developed countries (LDC), the proliferation of Free Trade Agreements (FTA,) and the digital economy. Using the Generalised Least Squares Random effects (GLS RE) and the Ordinary least squares (OLS) estimations with a sample size of …

The Pivot To Online Learning: A Case Study Of Efl Student Teachers’ Learning Experiences And Perceptions In China, Jingxin Cheng

Dissertations

Teaching and learning online was extensively adopted in English as a foreign language (EFL) teacher education program, as well in education of all levels in China with the advancement of the internet, multimedia information processing, cloud computing, and other information technologies since 1994. However, online education has remained more of a supplement to classroom education, and large-scale normal online education lacks cases and research in China. The COVID-19 pandemic caused profound change in higher education, with closures of campuses globally and migration of learning and teaching practices to online formats. The COVID-19 pandemic disrupted traditional teaching and learning activities, meanwhile, …

Software Developers’ Experiences With Call In The Context Of The Four Language Competencies (Reading, Writing, Listening, And Speaking) And Teacher And Learner Fit: A Qualitative Descriptive Study, Artem Kalyanov

Dissertations

Purpose: The purpose of this qualitative descriptive study was to explore how CALL software developers identify and describe their experiences with developing CALL software in the context of the four language competencies: reading, writing, listening, and speaking, along with teacher and learner fit.

Findings: The analysis of the collected data revealed six key findings that shed light on the developers’ experiences. The findings related to how CALL software developers combine different language competencies; how they implement continuous testing and evaluating of key elements of the language competencies; and how they ensure the development of a CALL program that is both …

Application Of A New Scale-Resolving Turbulence Model To Supersonic Retropropulsion Flows With Chemistry, Gabriel C. Nastac

Dissertations

Turbulent compressible flows are ubiquitous in many engineering applications of flight and propulsion. Computational fluid dynamics simulations are commonly performed to analyze these flows. Scale-resolving turbulence models inherently better capture various flow phenomena, including separation and mixing, as well as enable predictions of fluctuations, which can be critical for design compared to traditional steady-state turbulence models. In this work, new scale-resolving blended Partially-Averaged Navier-Stokes (BPANS) turbulence models are developed to account for compressibility effects and are employed to efficiently simulate turbulent compressible flows. Specifically, supersonic retropropulsion flows are investigated. Supersonic retropropulsion is a key technology for next-generation rockets. The new …

The Relationship Between Startups’ Early Adoption Of Digital Platforms And Startups’ Pre-Money Valuation, Bader Hassan Faqeeh

Dissertations

The objective of this study was to explore whether there was a significant positive relationship between startups’ early adoption of the digital platforms, namely, 1) mobile application, 2) a premium domain name website, and 3) the existence of active startup social media accounts, and startups’ pre-money valuation. To achieve this objective, this research used a relatively novel method in entrepreneurial research to collect data, whereby LinkedIn’s Sales Navigator was used along with an automation tool in order to send hundreds of automated connection and message requests to investors on LinkedIn who were sent a copy of the survey questions along …

A Novel Multi-Model Patient Similarity Network Driven By Federated Data Quality And Resource Profiling, Alramzana Nujum Navaz

Dissertations

Smart and Connected Health (SCH) is revolutionizing healthcare by leveraging extensive healthcare data for precise, personalized medicine. At its core, SCH relies on the concept of patient similarity, which involves the comparative analysis of newly encountered patients with those who exhibit comparable similarities from the existing patient cohort. Yet, this approach faces significant challenges, including data heterogeneity and dimensionality. Our research introduces a multi-dimensional Patient Similarity Network (PSN) Fusion model tailored to handle both static and dynamic features. The static data analysis focuses on extracting contextual information using Bidirectional Encoder Representations from Transformers (BERT), while dynamic features are captured through …

Advanced Traffic Video Analytics For Robust Traffic Accident Detection, Hadi Ghahremannezhad

Dissertations

Automatic traffic accident detection is an important task in traffic video analysis due to its key applications in developing intelligent transportation systems. Reducing the time delay between the occurrence of an accident and the dispatch of the first responders to the scene may help lower the mortality rate and save lives. Since 1980, many approaches have been presented for the automatic detection of incidents in traffic videos. In this dissertation, some challenging problems for accident detection in traffic videos are discussed and a new framework is presented in order to automatically detect single-vehicle and intersection traffic accidents in real-time.

First, …

Local Labor Markets Exposure To Artificial Intelligence, Greg Call

Dissertations

As more evidence builds that artificial intelligence (AI) is a new general-purpose technology driving a fourth industrial revolution, scholars have begun to consider its potential impact on labor markets. The current debate among researchers is centered on whether AI will ultimately produce net new job gains or losses and what type of workers will benefit or be displaced. While no consensus has developed yet within the literature on AI’s predicted net employment impact, a majority of studies are forecasting that a skill-biased technological change will occur.

This exploratory study contributes to the current literature by operationalizing Webb’s objective patent-based AI …

Mapping Programs To Equations, Hessamaldin Mohammadi

Dissertations

Extracting the function of a program from a static analysis of its source code is a valuable capability in software engineering; at a time when there is increasing talk of using AI (Artificial Intelligence) to generate software from natural language specifications, it becomes increasingly important to determine the exact function of software as written, to figure out what AI has understood the natural language specification to mean. For all its criticality, the ability to derive the domain-to-range function of a program has proved to be an elusive goal, due primarily to the difficulty of deriving the function of iterative statements. …

Reliable And Energy-Efficient 3d Nand Flash Storage System Design Using Run-Time Device And System Interaction, Md Raquibuzzaman

Dissertations

NAND Flash memory is a non-volatile solid-state data storage technology widely used in electronic devices such as smartphones, tablets, laptops, digital cameras, USB drives, solid-state drives (SSDs), autonomous vehicles, space applications, and data centers. NAND Flash memory-based SSDs are increasingly replacing the hard-disk drives (HDD) due to their high-density memory storage, low latency, low power consumption, and light weight. The NAND Flash memory has evolved from its planer 2D architecture to its contemporary 3D vertical layer architecture to meet the exponential storage demand. However, the 3D NAND architecture poses new reliability challenges, such as big block management, poly-Si-related read instability, …

Software Protection And Secure Authentication For Autonomous Vehicular Cloud Computing, Muhammad Hataba

Dissertations

Artificial Intelligence (AI) is changing every technology we deal with. Autonomy has been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected coined as Autonomous Vehicles (AVs). Moreover, researchers found a way to make more use of these enormous capabilities and introduced Autonomous Vehicles Cloud Computing (AVCC). In these platforms, vehicles can lend their unused resources and sensory data to join AVCC.

In this dissertation, we investigate security and privacy issues in AVCC. As background, we built our …

Digital Image Forensics Via Meta-Learning And Few-Shot Learning, Yuxi Shi

Dissertations

Digital images are a substantial portion of the information conveyed by social media, the Internet, and television in our daily life. In recent years, digital images have become not only one of the public information carriers, but also a crucial piece of evidence. The widespread availability of low-cost, user-friendly, and potent image editing software and mobile phone applications facilitates altering images without professional expertise. Consequently, safeguarding the originality and integrity of digital images has become a difficulty. Forgers commonly use digital image manipulation to transmit misleading information. Digital image forensics investigates the irregular patterns that might result from image alteration. …

Time-Dependent Photoionization Modeling Of Warm Absorbers In Active Galactic Nuclei, Dev Raj Sadaula

Dissertations

Warm absorber spectra are bound-bound and bound-free absorption features, seen in the X-ray and UV spectra from many active galactic nuclei (AGN). The widths and centroid energies of these features indicate they occur in outflowing gas moving with hundreds to thousands of km/s. Depending upon the energy and momentum of the outflow, it can affect the gas within the host galaxy. Thus, warm absorbers’ mass and energy budgets are of great interest. Estimates for these properties depend on models that connect the absorption features' observed strengths with the density, composition, and ionization state of the absorbing gas. Such models assume …

Application Of Deep Learning For Medical Sciences And Epidemiology Data Analysis And Diagnostic Modeling, Somenath Chakraborty

Dissertations

Machine Learning and Artificial Intelligence have made significant progress concurrent with new advancements in hardware and software technologies. Deep learning methods heavily utilize parallel computing and Graphical Processing Units(GPU). It is already used in many applications ranging from image classification, object detection, segmentation, cyber security problems and others. Deep Learning is emerging as a viable choice in dealing with today’s real-time medical problems. We need new methods and technologies in the field of Medical Science and Epidemiology for detecting and diagnosing emerging threats from new viruses such as COVID-19. The use of Artificial Intelligence in these domains is becoming more …

Military Instructors' Perspectives Of Integrating Instructional Multimedia Into Military Classrooms, Keontra Campbell

Dissertations

The United States Army has made efforts to meet the demand for digital technology. There is a continued need to train Soldiers with integrated multimedia instruction products to ensure soldiers are combat-ready. The purpose of this study was to investigate military instructors' lived experiences and perspectives on interactive multimedia instructional (IMI) product integrations' influence on students learning experiences and knowledge transfer and to understand the challenges instructors face, the strategies, needs, barriers, and the resources they use when integrating IMI products at a U.S. Army School of Excellence. The study uses a qualitative research design using a phenomenological approach. The …

Private Information Retrieval And Function Computation For Noncolluding Coded Databases, Sarah A. Obead

Dissertations

The rapid development of information and communication technologies has motivated many data-centric paradigms such as big data and cloud computing. The resulting paradigmatic shift to cloud/network-centric applications and the accessibility of information over public networking platforms has brought information privacy to the focal point of current research challenges. Motivated by the emerging privacy concerns, the problem of private information retrieval (PIR), a standard problem of information privacy that originated in theoretical computer science, has recently attracted much attention in the information theory and coding communities. The goal of PIR is to allow a user to download a message from a …

Resource Allocation For Heterogeneous Wireless Networks Of Devices With Multi-Connectivity, Monika Prakash

Dissertations

This dissertation contributes to designing an effective resource allocation scheme for multi-connectivity (MC) networks. MC is a feature that allows devices to utilize the radio resources from more than one base station simultaneously. With MC anticipated to play a key role in satisfying the stringent QoS requirements of the next-generation networks (5G/6G), it is crucial to efficiently allocate the resources across multiple connections of one or more radio access technologies (RATs).
Currently, there is a huge demand on the availability of radio spectrum resources with a large volume of different types of data traffic (Internet-of-things, human-based, machine-machine) traversing the internet. …

Management Of Data Brokers In Support Of Smart Community Applications, Shadha Tabatabai

Dissertations

The widespread use of smart devices has led to the Internet of Things (IoT) revolution. Big data generated by billions of devices must be analyzed to make better decisions. However, this introduces security, communication, and processing problems. To solve these problems, we develop algorithms to enhance the work of brokers. We focus our efforts on three problems.

In the first problem, brokers are used in the cloud along with Software Defined Network (SDN) switches. We formulate minimizing brokers’ load difference within a reconfiguration budget with the constraint of indivisible topics as an Integer Linear Programming (ILP) problem. We show that …

The Global Rise Of Online Devices, Cyber Crime And Cyber Defense: Enhancing Ethical Actions, Counter Measures, Cyber Strategy, And Approaches, Naresh Kshetri

Dissertations

The rise of online devices, online users, online shopping, online gaming, and online teaching has ultimately given rise to online attacks and online crimes. As cases of COVID-19 seem to increase day by day, so do online crimes and attacks (as many sectors and organizations went 100% online). Technological advancements and cyber warfare already generated many ethical issues, as internet users increasingly need ethical cyber defense strategies.

Individual internet users have challenges on their end; and on the other end, nation states (some secretly, some openly), are investing in robot weapons and autonomous weapons systems (AWS). New technologies have combined …

Employee Engagement, Brain-Based Psychological Safety, And The Sales Professional, Cheri Sherman

Dissertations

Purpose: The purpose of this correlational study was to determine what relationship, if any, existed between employee engagement and psychological safety as measured by the Utrecht Work Engagement Scale (UWES) and the Academy of Brain-based Leadership’s S.A.F.E.T.Y.™ Assessment and Pulse Survey domains of security, autonomy, fairness, esteem, and trust.

Methodology: A quantitative, correlational methodology was used for this study. The post-hoc sample comprised of 61 high-performing sales professionals working in California. Participants completed the three assessments online via SurveyMonkey. The data were analyzed using a Spearman correlation.

Findings: This study resulted in multiple findings, including a statistically significant relationship between …

Kg-Cnn: Augmenting Convolutional Neural Networks With Knowledge Graphs For Multi-Class Image Classification, Aidan O'Neill

Dissertations

Computer vision is slowly becoming more and more prevalent in daily life. Tesla has recently announced that it plans to scale up the manufacturing of their Robotaxis by 2024, with this increase in self-driving vehicles being just one example, the importance of computer vision is growing year by year. Vision can be easy to take for granted, as most humans grow up using vision as their primary way of absorbing environmental information. The way humans process and classify visual information differs significantly from how current computer vision systems process and organise visual information. The human brain can use its past …

Evaluating The Performance Impact Of Fine-Tuning Optimization Strategies On Pre-Trained Distilbert Models Towards Hate Speech Detection In Social Media, Aidan Mcgovern

Dissertations

Hate speech can be defined as forms of expression that incite hatred or encourage violence towards a person or group based on race, religion, gender, or sexual orientation. Hate speech has gravitated towards social media as its primary platform, and its propagation represents profound risks to both the mental well-being and physical safety of targeted groups. Countermeasures to moderate hate speech face challenges due to the volumes of data generated in social media, leading companies, and the research community to evaluate methods to automate its detection. The emergence of BERT and other pre-trained transformer-based models for transfer learning in the …

Performance Evaluation Of An Edge Computing Implementation Of Hyperledger Sawtooth For Iot Data Security, Sean Connolly

Dissertations

Blockchain offers a potential solution to some of the security challenges faced by the internet-of-things (IoT) by using its practically immutable ledger to store data transactions. However, past applications of blockchain in IoT encountered limitations in the rate at which transactions were committed to the chain as new blocks. These limitations were often the result of the time-consuming and computationally expensive consensus mechanisms found in public blockchains. Hyperledger Sawtooth is an open-source private blockchain platform that offers an efficient proof-of-elapsed-time (PoET) consensus mechanism. Sawtooth has performed well in benchmarks against other blockchains. However, a performance evaluation for a practical application …

Machine Learning Techniques For Network Analysis, Irfan Lateef

Dissertations

The network's size and the traffic on it are both increasing exponentially, making it difficult to look at its behavior holistically and address challenges by looking at link level behavior. It is possible that there are casual relationships between links of a network that are not directly connected and which may not be obvious to observe. The goal of this dissertation is to study and characterize the behavior of the entire network by using eigensubspace based techniques and apply them to network traffic engineering applications.

A new method that uses the joint time-frequency interpretation of eigensubspace representation for network statistics …

Novel Statistical Modeling Methods For Traffic Video Analysis, Hang Shi

Dissertations

Video analysis is an active and rapidly expanding research area in computer vision and artificial intelligence due to its broad applications in modern society. Many methods have been proposed to analyze the videos, but many challenging factors remain untackled. In this dissertation, four statistical modeling methods are proposed to address some challenging traffic video analysis problems under adverse illumination and weather conditions.

First, a new foreground detection method is presented to detect the foreground objects in videos. A novel Global Foreground Modeling (GFM) method, which estimates a global probability density function for the foreground and applies the Bayes decision rule …

Performance Evaluation Of Transportation Systems For Sustainability And Smart-Growth Of Cities: An Integrated Assessment Of Health Impacts, Ahmad Feizi

Dissertations

The performance of transportation systems is a significant component that influences the quality of life. The performance evaluation refers to a process of determining how well transportation systems perform regarding their intended goals and objectives. The advancement of information and communication technology and the integration between transportation systems and advanced technologies have directed more attention to the concept of smart cities. Smart cities are constituted of several interrelated components. Therefore, this offers comprehensive and integrated frameworks to evaluate the transportation performance and understanding of multifaceted interactions between the components from a transportation engineering perspective in four sections.

In the first …

Intelligent And Secure Fog-Aided Internet Of Drones, Jingjing Yao

Dissertations

Internet of drones (IoD), which utilize drones as Internet of Things (IoT) devices, deploys several drones in the air to collect ground information and send them to the IoD gateway for further processing. Computing tasks are usually offloaded to the cloud data center for intensive processing. However, many IoD applications require real-time processing and event response (e.g., disaster response and virtual reality applications). Hence, data processing by the remote cloud may not satisfy the strict latency requirement. Fog computing attaches fog nodes, which are equipped with computing, storage and networking resources, to IoD gateways to assume a substantial amount of …

Improving Multi-Threaded Qos In Clouds, Weiwei Jia

Dissertations

Multi-threading and resource sharing are pervasive and critical in clouds and data-centers. In order to ease management, save energy and improve resource utilization, multi-threaded applications from different tenants are often encapsulated in virtual machines (VMs) and consolidated on to the same servers. Unfortunately, despite much effort, it is still extremely challenging to maintain high quality of service (QoS) for multi-threaded applications of different tenants in clouds, and these applications often suffer severe performance degradation, poor scalability, unfair resource allocation, and so on.

The dissertation identifies the causes of the QoS problems and improves the QoS of multi-threaded execution with three …

Higher Education Business And Technology Leaders’ Behaviors That Drive Outcome Alignment, Katherine Lynch-Holmes

Dissertations

Higher education institutions (HEIs) face unprecedented challenges, including capacity alignment, financial sustainability, and even public confidence (Grajeck & Brooks, 2020; Grawe, 2019; Oblinger, 2019; Simone, 2020, Wheeler, 2020, Witt & Coyne, 2019). Financial challenges force HEIs to reduce costs by making decisions like cutting programs, laying off staff or merging institutions to reduce operating costs (Chen et al., 2019; Sellingo, 2017; Witt & Coyne, 2019). Higher education leaders (HELs) must act as trusted partners and broker technology to align processes, support, and outcomes (Luftman 2000; Petkovics, 2018; Reinitz, 2019). Unfortunately, higher education’s business-technology (BITA) alignment remains lower than other national …

An Evaluation On The Performance Of Code Generated With Webassembly Compilers, Raymond Phelan

Dissertations

WebAssembly is a new technology that is revolutionizing the web. Essentially it is a low-level binary instruction set that can be run on browsers, servers or stand-alone environments. Many programming languages either currently have, or are working on, compilers that will compile the language into WebAssembly. This means that applications written in languages like C++ or Rust can now be run on the web, directly in a browser or other environment. However, as we will highlight in this research, the quality of code generated by the different WebAssembly compilers varies and causes performance issues. This research paper aims to evaluate …